A novel workflow for the safe and effective integration of AI as supporting reader in double reading breast cancer screening: A large-scale retrospective evaluation
Abstract:Objectives
To evaluate the effectiveness of a novel strategy for using AI as a supporting reader for the detection of breast cancer in mammography-based double reading screening practice. Instead of replacing a human reader, here AI serves as the second reader only if it agrees with the recall/no-recall decision of the first human reader. Otherwise, a second human reader makes an assessment, enacting standard human double reading.
Design
Retrospective large-scale, multi-site, multi-device, evaluation study.
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